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    Home > Active Ingredient News > Study of Nervous System > Radiology: Evaluation of SSc-related ILD, we are one step closer

    Radiology: Evaluation of SSc-related ILD, we are one step closer

    • Last Update: 2021-07-27
    • Source: Internet
    • Author: User
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     Interstitial lung disease (ILD) is the main cause of morbidity and death in patients with systemic sclerosis (SSc)
    .


    High-resolution CT of the chest is the most reliable imaging method for detecting ILD


     Interstitial lung disease (ILD) is the main cause of morbidity and death in patients with systemic sclerosis (SSc)


    For disease monitoring, PFT measurement, especially forced vital capacity predicted by age and gender, is the main detection index


    Recently, a study published in the Journal of Radiology developed a deep learning-based method that can detect lung collapse based on the elastic registration of chest CT images obtained during follow-up, thereby making an assessment of the deterioration of SSc-ILD.


    This study retrospectively included SSc patients evaluated between January 2009 and October 2017.


    A total of 212 patients (median age 53 years old; interquartile range, 45-62 years old; 177 women) were included in this study: 138 cases (65%) in the training set, 34 cases (16%) in the validation set, and test set 40 cases (21%)


     

    The image CT shows the Jacobian of a patient with progressive and stable interstitial lung disease (ILD)
    .


    A, patients with progressive ILD


    The image CT shows the Jacobian of a patient with progressive and stable interstitial lung disease (ILD)


    This study shows that the elastic registration of CT scans combined with deep learning classifiers can be used to diagnose the morphological and functional deterioration of interstitial lung disease in patients with systemic sclerosis, providing a more comprehensive and accurate assessment of lung function for the clinic Of imaging methods


    Original source:

    Guillaume Chassagnon , Maria Vakalopoulou , Alexis Régent , et al.


    Guillaume Chassagnon , Maria Vakalopoulou , Alexis Régent , et al.


    DOI: 10.
    1148/radiol.
    2020200319 10.
    1148/radiol.
    2020200319 leave a message here
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